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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Interactive Visualization of Multi-Group Cross Sections on High-Fidelity Spatial Meshes

Core simulation tools utilizing Monte Carlo transport methods represent the 'Holy Grail' for nuclear reactor analysis. However, deterministic transport methods pose a number of advantages to Monte Carlo from a computational perspective, which seems likely to make these methods more viable in the near to intermediate term. Deterministic methods almost universally discretize the energy domain in a few to hundreds of energy groups. One of the key challenges for deterministic transport-based methods to be viable is accurate, reactor agnostic multi-group cross section generation. This paper describes tools for data processing and visualization of multigroup cross sections generated on high-fidelity spatial meshes from the OpenMC Monte Carlo code. Next generation deterministic transport reactor core modeling tools will require multi-group cross section (MGXS) generation on high-fidelity spatial meshes. High-fidelity MGXS are necessary for the accurate simulation of neutron physics in nuclear reactors with a high degree of spectral heterogeneity - e.g., large localized neutron flux gradients throughout a reactor core. Although many local (e.g., pin cell) approximations have been developed to model the scalar flux to compute spectral-averaged MGXS, these techniques cannot account for complex intra-pin and intra-assembly spatial self-shielding effects. Monte Carlo presents the most accurate method for reactor agnostic multi-group cross section generation since it does not require the use of local approximations to the flux. Monte Carlo has been proposed as a highly desirable framework for reactor agnostic cross section generation for many years. Monte Carlo methods can effectively embed all of the relevant spectral effects into the MGXS through the random particle tracking and interaction sampling processes. Previous work has applied MCNP and Serpent to compute few-group constants for diffusion calculations, and OpenMC to compute multi-group cross sections for transport-based methods. The primary difficulty with using Monte Carlo for MGXS generation is the tremendous computational resources required to adequately converge multi-group cross sections in each spatial region and energy group. Recent development of the OpenMC Monte Carlo code for high-performance computing platforms has made multigroup cross section generation from Monte Carlo more tractable in the foreseeable future. The recent release of OpenMC v0.7.1 includes a new Python-based module for MGXS generation. The MGXS generation module leverages many of the algorithms and features for 'big data' analysis of large tally datasets on complex spatial meshes. This paper describes the data management workflow and visualization tools which have been developed to explore the plethora of MGXS data generated with OpenMC. It is the authors' hope that the development of the visualization tool described in this paper will ultimately enable the design of machine learning algorithms to accelerate the convergence rate of high-fidelity multi-group cross section generated with Monte Carlo. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Fully Implicit Conjugate Heat Transfer Analysis of the ARC-Class Vacuum Vessel

The coupled simulation of fusion reactor blankets including neutronics, thermal-hydraulics and thermo-mechanics is expected to speed up the design cycle of fusion reactor design concepts. In this work we demonstrate tight implicit coupling of conjugate heat transfer using the open-source Computational Fluid Dynamics software OpenFOAM for thermo-fluid mechanics and Diablo for thermo-solid mechanics. The heat transfer analysis is augmented by volumetric energy deposition from neutronic calculations using the Monte Carlo N-particle code on both solid and fluid parts of the vacuum vessel. An additional heat flux is imposed on the first wall estimated from the design power of the reactor. The tight coupling is realized through the open-source coupling library, preCICE, and tested on the vacuum vessel of the affordable, robust, compact reactor design by Commonwealth Fusion Systems. The features of the coupling and the influence of different coupling parameters such as coupling schemes, acceleration techniques and convergence criterion are discussed. The coupled simulation results are compared to a thermal-hydraulics simulation which includes only the fluid domains (the liquid immersion molten salt blanket and cooling channel) to demonstrate usefulness of a coupled simulation. Further analysis is performed to identify regions of hot spots for subsequent design improvement. This introduces the outline for integrating conjugate electromagnetics and fluid/solid mechanics (e.g., allow for deformation of the cooling channel walls) with our present approach for future analysis.

Sircar, Arpan↗
DOE OSTI2024

The Evaluation of Machine Learning Techniques for Isotope Identification Contextualized by Training and Testing Spectral Similarity

Precise gamma-ray spectral analysis is crucial in high-stakes applications, such as nuclear security. Research efforts toward implementing machine learning (ML) approaches for accurate analysis are limited by the resemblance of the training data to the testing scenarios. The underlying spectral shape of synthetic data may not perfectly reflect measured configurations, and measurement campaigns may be limited by resource constraints. Consequently, ML algorithms for isotope identification must maintain accurate classification performance under domain shifts between the training and testing data. To this end, four different classifiers (Ridge, Random Forest, Extreme Gradient Boosting, and Multilayer Perceptron) were trained on the same dataset and evaluated on twelve other datasets with varying standoff distances, shielding, and background configurations. A tailored statistical approach was introduced to quantify the similarity between the training and testing configurations, which was then related to the predictive performance. Wilcoxon signed-rank tests revealed that the OVR-wrapped XGB significantly outperformed the other algorithms, with confidence levels of 99.0% or above for the 133Ba, 60Co, 137Cs, and 152Eu sources. The findings from this work are significant as they outline techniques to promote the development of robust ML-based approaches for isotope identification.

domain adaptation↗
NASA NTRS2021

EnDEVR: An Environment for Data Engineering in VR

Organizations within the public and private sectors are looking to improve their data science operations for research, development, and operational purposes. As this interest in data science grows, so too does interest in tools and programs that facilitating such operations. This paper presents EnDEVR, the Environment for Data Engineering in Virtual Reality, a user-extensible system that allows for the execution of custom data science functions. We describe the user-centered design process for the EnDEVR system, based on the needs of subject matter experts within the aerospace and aviation industries. Fundamental to this design is a method for users to integrate their existing analysis code (that may leverage third-party vendors) as usable objects in the virtual environment; this allows organizations to operate without the price tag and lifetime obligations associated with commercial data science toolkits, a concept known as “vendor lock-in”. We then present our system design with iterative implementations, and conclude with lessons learned. The presented work may provide insight into future user-centered design processes for VR applications, particularly for digital transformation stakeholders to circumvent vendor lock-in.

Human-centered computing↗
DOE OSTI2016

An Investigation of Passive and Semi-Active Tuned Mass Dampers for a Tension Leg Platform Floating Offshore Wind Turbine in ULS Conditions

Offshore Wind Turbines (OWTs) are subjected to complex external loadings caused by combined wind and wave sources. The application of structural damping control techniques to OWTs using Tuned Mass Dampers (TMDs) has shown to be effective in reducing the integrated system loads and accelerations. In this work, the impact of passive and semi-active (S-A) TMD’s applied to both fixed-bottom (monopile) and floating (tension leg platform) OWTs are evaluated under the Fatigue Limit State (FLS) and Ultimate Limit State (ULS). Different S-A control logics like ON/OFF state damping based on the ground hook (GH) control policy are implemented, and the frequency response of each algorithm is investigated. It is shown that the performance of each algorithm varies according to the load conditions such as FLS (normal operation) and ULS (idling state). Fully-coupled time domain simulations are conducted through the developed simulation tool for structural control integrated into the high-fidelity wind turbine design code, FASTv8. Compared to the passive TMD, it is shown that a S-A TMD results in higher load reductions, as well as, smaller strokes under both FLS and ULS conditions. In FLS analysis, the S-A TMD using Displacement Based Ground Hook (DB-GH) control is capable of reducing the fore-aft and side-to-side damage equivalent loads for the monopile substructure by approximately 12 % and 64 %, respectively. The ultimate loads at the tower base for the floating substructure (TLP) are also reduced by 9% with S-A TMD followed by Inverse Velocity Based Ground Hook control (IVB-GH). The dynamic characteristics and practical feasibility of a magnetorheological (MR) damper (for S-A control) are also evaluated.

17 WIND ENERGY↗
DOE OSTI2016

Time-frequency energy density precipitation method for time-of-flight extraction of narrowband Lamb wave detection signals

The time-of-flight of the Lamb wave provides an important basis for defect evaluation in metal plates and is the input signal for Lamb wave tomographic imaging. However, the time-of-flight can be difficult to acquire because of the Lamb wave dispersion characteristics. This work proposes a time-frequency energy density precipitation method to accurately extract the time-of-flight of narrowband Lamb wave detection signals in metal plates. In the proposed method, a discrete short-time Fourier transform is performed on the narrowband Lamb wave detection signals to obtain the corresponding discrete time-frequency energy density distribution. The energy density values at the center frequency for all discrete time points are then calculated by linear interpolation. Next, the time-domain energy density curve focused on that center frequency is precipitated by least squares fitting of the calculated energy density values. Finally, the peak times of the energy density curve obtained relative to the initial pulse signal are extracted as the time-of-flight for the narrowband Lamb wave detection signals. An experimental platform is established for time-of-flight extraction of narrowband Lamb wave detection signals, and sensitivity analysis of the proposed time-frequency energy density precipitation method is performed in terms of propagation distance, dispersion characteristics, center frequency, and plate thickness. For comparison, the widely used Hilbert–Huang transform method is also implemented for time-of-flight extraction. The results show that the time-frequency energy density precipitation method can accurately extract the time-of-flight with relative error of <1% and thus can act as a universal time-of-flight extraction method for narrowband Lamb wave detection signals.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

PilN binding modulates the structure and binding partners of the Pseudomonas aeruginosa type IVa pilus protein PilM

Pseudomonas aeruginosa is an opportunistic bacterial pathogen that expresses type IVa pili. The pilus assembly system, which promotes surface-associated twitching motility and virulence, is composed of inner and outer membrane subcomplexes, connected by an alignment subcomplex composed of PilMNOP. PilM binds to the N terminus of PilN, and we hypothesize that this interaction causes functionally significant structural changes in PilM. To characterize this interaction, we determined the crystal structures of PilM and a PilM chimera where PilM was fused to the first 12 residues of PilN (PilM·PilN(1–12)). Structural analysis, multiangle light scattering coupled with size exclusion chromatography, and bacterial two-hybrid data revealed that PilM forms dimers mediated by the binding of a novel conserved motif in the N terminus of PilM, and binding PilN abrogates this binding interface, resulting in PilM monomerization. Structural comparison of PilM with PilM·PilN(1–12) revealed that upon PilN binding, there is a large domain closure in PilM that alters its ATP binding site. Using biolayer interferometry, we found that the association rate of PilN with PilM is higher in the presence of ATP compared with ADP. Bacterial two-hybrid data suggested the connectivity of the cytoplasmic and inner membrane components of the type IVa pilus machinery in P. aeruginosa , with PilM binding to PilB, PilT, and PilC in addition to PilN. Pull-down experiments demonstrated direct interactions of PilM with PilB and PilT. As a result, we propose a working model in which dynamic binding of PilN facilitates functionally relevant structural changes in PilM.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Structure and energetics of pairwise interactions between proteasome subunits RPN2, RPN13, and ubiquitin clarify a substrate recruitment mechanism

This work presents that the 26S proteasome is a large cellular assembly that mediates the selective degradation of proteins in the nucleus and cytosol and is an established target for anticancer therapeutics. Protein substrates are typically targeted to the proteasome through modification with a polyubiquitin chain, which can be recognized by several proteasome-associated ubiquitin receptors. One of these receptors, RPN13/ADRM1, is recruited to the proteasome through direct interaction with the large scaffolding protein RPN2 within the 19S regulatory particle. To better understand the interactions between RPN13, RPN2, and ubiquitin, we used human proteins to map the RPN13-binding epitope to the C-terminal 14 residues of RPN2, which, like ubiquitin, binds the N-terminal pleckstrin-like receptor of ubiquitin (PRU) domain of RPN13. We also report the crystal structures of the RPN13 PRU domain in complex with peptides corresponding to the RPN2 C terminus and ubiquitin. Through mutational analysis, we validated the RPN2-binding interface revealed by our structures and quantified binding interactions with surface plasmon resonance and fluorescence polarization. In contrast to a previous report, we find that RPN13 binds ubiquitin with an affinity similar to that of other proteasome-associated ubiquitin receptors and that RPN2, ubiquitin, and the deubiquitylase UCH37 bind to RPN13 with independent energetics. In conclusion, these findings provide a detailed characterization of interactions that are important for proteasome function, indicate ubiquitin affinities that are consistent with the role of RPN13 as a proteasomal ubiquitin receptor, and have major implications for the development of novel anticancer therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Destructive Analysis of TRISO Particles: Crush/Burn/Leach Followed by Davies-Gray Titration and IDMS

The accurate accounting of nuclear materials is a cornerstone of international nuclear safeguards. One emerging challenge in this domain is the fabrication of TRIstructural ISOtropic (TRISO) particle fuels. Although these innovative fuel forms are critical for advanced reactor applications, their robust refractory ceramics and coating compositions present significant obstacles to destructive analysis (DA) methods. Ensuring full and quantitative recovery from these particles is essential for accurate mass accountancy. The current study was initiated to address these challenges, first by validating a previously established destructive method developed by Oak Ridge National Laboratory (ORNL) for the quantitative recovery of uranium from TRISO particles and then following that process with uranium content determination through isotope dilution mass spectrometry (IDMS) and Davies-Gray titration. This study expands on the scope of a digestive method that was developed under the Advanced Gas Reactor Fuel Development and Qualification program and is currently implemented in both the Coated Particle Fuel Development Laboratory and Irradiated Fuels Examination Laboratory at ORNL. The success of the previous Advanced Gas Reactor work relied on developing a DA method to evaluate the fabrication process and reactor experiments. The methodology described in this report was designed to rigorously investigate the efficacy of the crush/burn/leach sample preparation of TRISO particles; it aims to quantify uranium recovery while also assessing the effects of TRISO constituents (e.g., silicon and zirconium) on analytical precision and accuracy. By comparing the results from the titration method and IDMS, we sought to determine whether existing analytical procedures accepted by the International Atomic Energy Agency (IAEA) could be effectively translated to TRISO fuel forms. The team employed an approach that involved processing replicate TRISO samples, optimizing the milling (i.e., crushing) step and performing serial leaches. The elemental composition of the analytical samples was examined to prepare for interference studies in the second year of this project. The integration of gamma spectrometry to verify residual uranium activity further strengthened the validation. Statistical methods were applied to the collected data to evaluate the uncertainties arising from sampling, sample preparation and uranium quantification. These uncertainties were then compared to the IAEA’s international target values (ITVs). Additional data collected in upcoming project work will strengthen the uncertainty estimates. Ultimately, it is hoped that this project will contribute materially to the body of work related to characterization of TRISO based fuels for the purpose of material accountancy and its applications to international safeguards.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Thermal perturbation of NMR properties in small polar and non-polar molecules

Water is an important constituent in an abundant number of chemical systems; however, its presence complicates the analysis of in situ 1 H MAS NMR investigations due to water’s ease of solidification and vaporization, the large changes in mobility, affinity for hydrogen bonding interactions, etc., that are reflected by dramatic changes in temperature-dependent chemical shielding. To understand the signatures of water and other small molecules in complex environments, in particular how water interacts with the other molecules, in this work the thermally-perturbed NMR properties of water are investigated in detail by in situ MAS NMR. Our results substantially extend the previously published temperature-dependent 1 H and 17 O chemical shifts, linewidths, and spin-lattice relaxation times over a much wider range of temperatures and with significantly enhanced thermal resolution. The following major results are obtained: Hydrogen bonding is clearly shown to weaken at elevated temperatures in both 1 H and 17 O spectra, showing an increase in chemical shielding. At low temperatures, tetrahedral domains of H-bonding networks are evidenced and the observation of solid ice is made under in situ MAS conditions. The 1 H chemical shift properties in other small polar and non-polar molecules have also been described over a range of temperatures, showing the dramatic effect hydrogen bonding perturbation. Gas phase species are described where chemical exchange between gas and liquid phases plays an important role on the observed NMR shifts. The results disclosed herein lay the foundation for a clearer interpretation of complex systems during the increasingly popular in situ NMR characterization at elevated temperatures and pressures for studying chemical systems containing water molecules.

17O NMR↗
DOE OSTI2019

Structural determinants for accurate dephosphorylation of RNA polymerase II by its cognate C-terminal domain (CTD) phosphatase during eukaryotic transcription

The C-terminal domain (CTD) of RNA polymerase II contains a repetitive heptad sequence (YSPTSPS) whose phosphorylation states coordinate eukaryotic transcription by recruiting protein regulators. The precise placement and removal of phosphate groups on specific residues of the CTD are critical for the fidelity and effectiveness of RNA polymerase II–mediated transcription. During transcriptional elongation, phosphoryl-Ser 5 (pSer 5 ) is gradually dephosphorylated by CTD phosphatases, whereas Ser 2 phosphorylation accumulates. Using MS, X-ray crystallography, protein engineering, and immunoblotting analyses, in this work we investigated the structure and function of SSU72 homolog, RNA polymerase II CTD phosphatase (Ssu72, from Drosophila melanogaster ), an essential CTD phosphatase that dephosphorylates pSer 5 at the transition from elongation to termination, to determine the mechanism by which Ssu72 distinguishes the highly similar pSer 2 and pSer 5 CTDs. We found that Ssu72 dephosphorylates pSer 5 effectively but only has low activities toward pSer 7 and pSer 2 . The structural analysis revealed that Ssu72 requires that the proline residue in the substrate's SP motif is in the cis configuration, forming a tight β-turn for recognition by Ssu72. We also noted that residues flanking the SP motif, such as the bulky Tyr 1 next to Ser 2 , prevent the formation of such configuration and enable Ssu72 to distinguish among the different SP motifs. The phosphorylation of Tyr 1 further prohibited Ssu72 binding to pSer 2 and thereby prevented untimely Ser 2 dephosphorylation. Our results reveal critical roles for Tyr 1 in differentiating the phosphorylation states of Ser 2 /Ser 5 of CTD in RNA polymerase II that occur at different stages of transcription.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Haloferax volcanii archaeosortase is required for motility, mating, and C-terminal processing of the S-layer glycoprotein: Haloferax volcanii archeosortase

Cell surfaces are decorated by a variety of proteins that facilitate interactions with their environments and support cell stability.These secreted proteins are anchored to the cell by mechanisms that are diverse, and, in archaea, poorly understood. Recently published in silico data suggest that in some species a subset of secreted euryarchaeal proteins, which includes the S-­layer glycoprotein, is processed and covalently linked tot he cell membrane by enzymes referred to as archaeosortases. In silico work led to the proposal that an independent, sortase-like system for proteolysis-coupled carboxy-terminal lipid modification exists in bacteria (exosortase) and archaea (archaeosortase). Here, we provide the first in vivo characterization of an archaeosortase in the haloarchaeal model organism Haloferax volcanii. Deletion of the artA gene (HVO_0915) resulted in multiple biological phenotypes: (a) poor growth, especially under low-salt conditions, (b) alterations in cell shape and the S-layer, (c) impaired motility, suppressors of which still exhibit poor growth, and (d) impaired conjugation. We studied one of the ArtA substrates, the S-layer glycoprotein, using detailed proteomic analysis. While the carboxy-terminal region of S-layer glycoproteins, consisting of a threonine-rich O-glycosylated region followed by a hydrophobic transmembrane helix, has been notoriously resistant to any proteomic peptide identification, we were able to identify two overlapping peptides from the transmembrane domain present in the ΔartA strain but not in the wild-type strain. This clearly shows that ArtA is involved in carboxy-terminal posttranslational processing of the S-layer glycoprotein. As it is known from previous studies that a lipid is covalently attached to the carboxy-terminal region of the S-layer glycoprotein, our data strongly support the conclusion that archaeosortase functions analogously to sortase, mediating proteolysis-coupled, covalent cell surface attachment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Excited Baryon Structure Using Exclusive Reactions with CLAS12

Studying excited nucleon structure through exclusive electroproduction reactions is an important avenue for exploring the nature of the non-perturbative strong interaction. Electrocouplings for $N^*$ states in the mass range below 1.8~GeV have been determined from analyses of CLAS $\pi N$, $\eta N$, and $\pi \pi N$ data. This work made it clear that consistency of independent analyses of exclusive channels with different couplings and non-resonant backgrounds but the same $N^*$ electro-excitation amplitudes, is essential to have confidence in the extracted results. In terms of hadronic coupling, many high-lying $N^*$ states preferentially decay through the $\pi \pi N$ channel instead of $\pi N$. Data from the $KY$ channels will therefore be critical to provide an independent analysis to compare the extracted electrocouplings for the high-lying $N^*$ states against those determined from the $\pi N$ and $\pi \pi N$ channels. A program to study excited $N^*$ decays to non-strange and strange exclusive final states using CLAS12 will measure differential cross sections to be used as input to extract the $\gamma_vNN^*$ transition form factors for the most prominent $N^*$ states in the range of invariant energy $W$ up 3~GeV in the virtually unexplored domain of momentum transfers $Q^2$ up to 12~GeV$^2$.

Carman, Daniel↗
DOE OSTI2017

DE-NE0000724 - Research Performance Final Report - Investigation of Thermal Aging Effects on the Evolution of Microstructure and Mechanical Properties of Cast Duplex Stainless Steels

This report details the research activities carried out under DOE-NEUP award number DE-NE0000724 concerning the evolution of structural and mechanical properties during thermal aging of CF–3 and CF–8 cast duplex stainless steels (CDSS). The overall objective of this project was to use state-of-the-art characterization techniques to elucidate trends and phenomena in the mechanical and structural evolution of cast duplex stainless steels (CDSS) during thermal aging. These steels are commonly used as structural materials in commercial light water nuclear power plants, undergoing aging for decades in operation as cooling water pipes, pump casings, valve bodies, etc. During extended exposure to these conditions, CDSS are known to undergo a change in mechanical properties resulting in a loss of ductility, i.e. embrittlement. While it is generally accepted that structural changes within the ferrite phase, such as decomposition into iron (Fe)-rich and chromium (Cr)-rich domains, lead to the bulk embrittlement of the steels, many questions remain as to the mechanisms of embrittlement at multiple length scales. This work is intended to shed insight into the atomic level composition changes, associated kinetic mechanisms, and effects of changing phase structure on micro- and nano-scale deformation that lead to loss of impact toughness and tensile ductility in these steels. In general, this project provides a route to answer some of these major questions using techniques such as 3-dimensional (3-D) atom probe tomography (APT) and real-microstructure finite element method (FEM) modeling, which were not readily available when these steels were originally selected for service in light water reactors. Mechanical properties evaluated by Charpy V-notch impact testing (CVN), tensile testing, and microhardness and nanohardness measurements were obtained for each condition and compared with the initial baseline properties to view trends in deformation behavior during aging. Concurrent analysis of the microstructure and nanostructure by atom probe tomography (APT) and transmission electron microscopy (TEM) provide mechanistic insight into the kinetic and mechanical behavior occurring on the nano-scale. The presence and morphology of the ferrite, austenite, and carbide phases have been characterized, and formation of new phases during aging, including spinodal decomposition products (α- and α'-ferrite) and G-phase, have been observed. The mechanical and structural characterization have been used to create accurate FEM models based on the real micro- and nano-structures of the systems. These models provide new insight into the local deformation behavior of these steels and the effects of each individual phase (including ferrite, austenite, carbides, and spinodal decomposition products) on the evolving bulk mechanical behavior of the system. The project was divided into three major tasks: 1. Initial Microstructure and Mechanical Property Survey and Initiate Heat Treatment; 2. Microstructural Characterization and Mechanical Property Testing During Aging; and 3. Microstructure-based Finite Element Modeling. Each of these tasks was successfully executed, resulting in reliable data and analysis that add to the overall body of work on the CDSS materials. Baseline properties and aging trends in mechanical data confirm prior observations and add new insights into the mechanical behavior of the steels. Structural characterization on multiple length scales provides new information on phase changes occurring during aging and sheds light on the kinetic processes occurring at the atomic scale. Furthermore, a combination of mechanical testing and microstructural characterization techniques was utilized to design FEM models of local deformation behavior of the ferrite and austenite phases, providing valuable new information regarding the effects of each of the microstructural components on the hardening and embrittlement processes. The data and analysis presented in this report and the publication associated with this project (§V) increase the understanding of aging and deformation in CF–3 and CF–8 steels. These results provide valuable information that can be utilized to aid in making informed decisions regarding the ongoing use of these steels in commercial nuclear infrastructure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2004

Adjoint Algorithm for CAD-Based Shape Optimization Using a Cartesian Method

Adjoint solutions of the governing flow equations are becoming increasingly important for the development of efficient analysis and optimization algorithms. A well-known use of the adjoint method is gradient-based shape optimization. Given an objective function that defines some measure of performance, such as the lift and drag functionals, its gradient is computed at a cost that is essentially independent of the number of design variables (geometric parameters that control the shape). More recently, emerging adjoint applications focus on the analysis problem, where the adjoint solution is used to drive mesh adaptation, as well as to provide estimates of functional error bounds and corrections. The attractive feature of this approach is that the mesh-adaptation procedure targets a specific functional, thereby localizing the mesh refinement and reducing computational cost. Our focus is on the development of adjoint-based optimization techniques for a Cartesian method with embedded boundaries.12 In contrast t o implementations on structured and unstructured grids, Cartesian methods decouple the surface discretization from the volume mesh. This feature makes Cartesian methods well suited for the automated analysis of complex geometry problems, and consequently a promising approach to aerodynamic optimization. Melvin et developed an adjoint formulation for the TRANAIR code, which is based on the full-potential equation with viscous corrections. More recently, Dadone and Grossman presented an adjoint formulation for the Euler equations. In both approaches, a boundary condition is introduced to approximate the effects of the evolving surface shape that results in accurate gradient computation. Central to automated shape optimization algorithms is the issue of geometry modeling and control. The need to optimize complex, "real-life" geometry provides a strong incentive for the use of parametric-CAD systems within the optimization procedure. In previous work, we presented an effective optimization framework that incorporates a direct-CAD interface. In this work, we enhance the capabilities of this framework with efficient gradient computations using the discrete adjoint method. We present details of the adjoint numerical implementation, which reuses the domain decomposition, multigrid, and time-marching schemes of the flow solver. Furthermore, we explain and demonstrate the use of CAD in conjunction with the Cartesian adjoint approach. The final paper will contain a number of complex geometry, industrially relevant examples with many design variables to demonstrate the effectiveness of the adjoint method on Cartesian meshes.

Nemec, Marian↗
NASA NTRS2012

Extension of the Time-Spectral Approach to Overset Solvers for Arbitrary Motion

Forced periodic flows arise in a broad range of aerodynamic applications such as rotorcraft, turbomachinery, and flapping wing configurations. Standard practice involves solving the unsteady flow equations forward in time until the initial transient exits the domain and a statistically stationary flow is achieved. It is often required to simulate through several periods to remove the initial transient making unsteady design optimization prohibitively expensive for most realistic problems. An effort to reduce the computational cost of these calculations led to the development of the Harmonic Balance method [1, 2] which capitalizes on the periodic nature of the solution. The approach exploits the fact that forced temporally periodic flow, while varying in the time domain, is invariant in the frequency domain. Expanding the temporal variation at each spatial node into a Fourier series transforms the unsteady governing equations into a steady set of equations in integer harmonics that can be tackled with the acceleration techniques afforded to steady-state flow solvers. Other similar approaches, such as the Nonlinear Frequency Domain [3,4,5], Reduced Frequency [6] and Time-Spectral [7, 8, 9] methods, were developed shortly thereafter. Additionally, adjoint-based optimization techniques can be applied [10, 11] as well as frequency-adaptive methods [12, 13, 14] to provide even more flexibility to the method. The Fourier temporal basis functions imply spectral convergence as the number of harmonic modes, and correspondingly number of time samples, N, is increased. Some elect to solve the equations in the frequency domain directly, while others choose to transform the equations back into the time domain to simplify the process of adding this capability to existing solvers, but each harnesses the underlying steady solution in the frequency domain. These temporal projection methods will herein be collectively referred to as Time-Spectral methods. Time-Spectral methods have demonstrated marked success in reducing the computational costs associated with simulating periodic forced flows, but have yet to be fully applied to overset or Cartesian solvers for arbitrary motion with dynamic hole-cutting. Overset and Cartesian grid methodologies are versatile techniques capable of handling complex geometry configurations in practical engineering applications, and the combination of the Time-Spectral approach with this general capability potentially provides an enabling new design and analysis tool. In an arbitrary moving-body scenario for these approaches, a Lagrangian body moves through a fixed Eulerian mesh and mesh points in the Eulerian mesh interior to the solid body are removed (cut or blanked), leaving a hole in the Eulerian mesh. During the dynamic motion some gridpoints in the domain are blanked and do not have a complete set of time-samples preventing a direct implementation of the Time-Spectral method. Murman[6] demonstrated the Time-Spectral approach for a Cartesian solver with a rigid domain motion, wherein the hole cutting remains constant. Similarly, Custer et al. [15, 16] used the NASA overset OVERFLOW solver and limited the amount of relative motion to ensure static hole-cutting and interpolation. Recently, Mavriplis and Mundis[17] demonstrated a qualitative method for applying the Time-Spectral approach to an unstructured overset solver for arbitrary motion. The goal of the current work is to develop a robust and general method for handling arbitrary motion with the Time-Spectral approach within an overset or Cartesian mesh method, while still approaching the spectral convergence rate of the original Time-Spectral approach. The viscous OVERFLOW solver will be augmented with the new Time-Spectral algorithm and the capability of the method for benchmark problems in rotorcraft and turbomachinery will be demonstrated. This abstract begins with a brief synopsis of the Time-Spectral approach for overset grids and provides details of e current approach to allow for arbitrary motion. Model problem results in one and two dimensions are included to demonstrate the viability of the method and the convergence properties. Section IV briefly outlines the implementation into the OVERFLOW solver, and the abstract closes with a description of the benchmark test cases which will be included in the final paper.

Leffell, Joshua Isaac↗
NASA NTRS2013

Evidence Report: Risk of Inadequate Human-Computer Interaction

Human-computer interaction (HCI) encompasses all the methods by which humans and computer-based systems communicate, share information, and accomplish tasks. When HCI is poorly designed, crews have difficulty entering, navigating, accessing, and understanding information. HCI has rarely been studied in an operational spaceflight context, and detailed performance data that would support evaluation of HCI have not been collected; thus, we draw much of our evidence from post-spaceflight crew comments, and from other safety-critical domains like ground-based power plants, and aviation. Additionally, there is a concern that any potential or real issues to date may have been masked by the fact that crews have near constant access to ground controllers, who monitor for errors, correct mistakes, and provide additional information needed to complete tasks. We do not know what types of HCI issues might arise without this "safety net". Exploration missions will test this concern, as crews may be operating autonomously due to communication delays and blackouts. Crew survival will be heavily dependent on available electronic information for just-in-time training, procedure execution, and vehicle or system maintenance; hence, the criticality of the Risk of Inadequate HCI. Future work must focus on identifying the most important contributing risk factors, evaluating their contribution to the overall risk, and developing appropriate mitigations. The Risk of Inadequate HCI includes eight core contributing factors based on the Human Factors Analysis and Classification System (HFACS): (1) Requirements, policies, and design processes, (2) Information resources and support, (3) Allocation of attention, (4) Cognitive overload, (5) Environmentally induced perceptual changes, (6) Misperception and misinterpretation of displayed information, (7) Spatial disorientation, and (8) Displays and controls.

Kritina Holden↗
DOE OSTI2022

GDSA Framework Development and Process Model Integration FY2022

The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Spent Fuel & Waste Disposition (SFWD) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). A high priority for SFWST disposal R&D is disposal system modeling (Sassani et al. 2021). The SFWST Geologic Disposal Safety Assessment (GDSA) work package is charged with developing a disposal system modeling and analysis capability for evaluating generic disposal system performance for nuclear waste in geologic media. This report describes fiscal year (FY) 2022 advances of the Geologic Disposal Safety Assessment (GDSA) performance assessment (PA) development groups of the SFWST Campaign. The common mission of these groups is to develop a geologic disposal system modeling capability for nuclear waste that can be used to assess probabilistically the performance of generic disposal options and generic sites. The modeling capability under development is called GDSA Framework (pa.sandia.gov). GDSA Framework is a coordinated set of codes and databases designed for probabilistically simulating the release and transport of disposed radionuclides from a repository to the biosphere for post-closure performance assessment. Primary components of GDSA Framework include PFLOTRAN to simulate the major features, events, and processes (FEPs) over time, Dakota to propagate uncertainty and analyze sensitivities, meshing codes to define the domain, and various other software for rendering properties, processing data, and visualizing results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗